“Is This Even You or Some AI Chatbot?” – Why Student Engagement Needs to Evolve

The email went out. It was part of a carefully crafted mail merge—one of many sent that day. Within minutes, a response arrived:

“I already filled this out. Is this even you or some AI chatbot?”

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For enrollment professionals and student success teams, this is an all-too-familiar moment. A well-intended outreach effort lands flat, leaving students confused, frustrated, or disengaged. The reality? Higher education engagement strategies haven’t kept pace with student expectations.

Even in the day and age of CRM automation and AI, many schools are still stuck doing manual or semi-automated communication outreaches—like basic mail merges—which are no longer enough.

Today’s students expect personalized, real-time interactions that reflect their unique needs. Institutions that fail to adapt risk low engagement, missed enrollment targets, and higher attrition rates.

Before I start, I want to say that AI is not the fix to all problems, and much work needs to be completed to unlock the flywheel it brings. Many schools are still in the mindset of doing the work described above. It will require rethinking processes and how things are done. There will be some ups and downs, but seeing meaningful student outcomes is well worth it. You need to have a mindset of progress, not perfection in AI, and when it comes to Agentic AI, think of yourself in your first career job; there was likely some hand-holding involved. The same is true with AI; it is only as good as the training, instruction, and information provided.

I'm talking as someone who builds AI agents and workflows daily. I am giving you my unvarnished view of working in higher education, focusing on data science & operational improvement since 2010. I am also sharing some recent wisdom I have obtained by joining Element451. Element supports over 260 colleges and universities with an AI-first mindset within our company and in our products and solutions. We offer an All-in-One, AI-first student engagement platform with agentic AI agents on top of a world-class CRM. We work with institutions to help them understand and implement AI-driven solutions that enhance the student journey.

In this pursuit to move the industry along, I have crafted a three-part series on AI Readiness & Adoption in Higher Education, focusing on the Student Success Lifecycle. This critical pillar ensures that institutions can better engage, retain, and support students. The other two pillars to be explored are the Operational Service Model and Strategic Impact and Governance.

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Why the Student Success Lifecycle Matters

Higher education institutions are facing increasing challenges:

• Declining enrollments require more effective student engagement strategies. Data from the National Student Clearinghouse Research Center shows that enrollment of 18-year-old freshmen has dropped by 5% this fall semester.
• Student expectations for personalization have never been higher. The Department of Education highlights that 75% of students report feeling motivated and engaged in personalized learning environments—compared to just 30% in traditional classrooms—demonstrating that students now expect a personalized experience tailored to their individual needs inside and outside the classrom.
• Retention pressures demand proactive intervention to support at-risk students with only 68.2% of first-year students return to the same institution for their second year

AI-driven tools can provide personalized communication, predictive analytics, and proactive student support, transforming how institutions connect with students throughout their journey. Many of the 61 college and university closures since 2023 could have avoided their fate by focusing on this.

Now, let's transition into the five stages of AI Adoption in the Student Lifecycle. As you read these, your institution might fall into one, and your department might be ahead of the curve.

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The Five Stages of AI Adoption in the Student Lifecycle

1. Not Ready – Manual & Semi-Automated Processes

• Current Practices: Institutions rely on mail merges, bulk email templates, and manual student tracking—often leading to disengagement and miscommunication.
• Common Issues: Responses like “Didn’t I already do this?” or “Who is this from?” create friction in the student experience.
• AI to Explore: Basic AI chatbots that answer FAQs, reducing staff workload on repetitive inquiries and ensuring consistent messaging.

2. Early Stage – Basic Automation & Student Milestone Triggers

• Current Practices: Schools use pre-scheduled CRM email campaigns based on application deadlines but lack personalization.
• Common Issues: Students feel like they’re receiving generic, robotic emails that don’t acknowledge their past interactions.
• AI to Explore: Conversational AI chatbots with natural language processing (NLP) to guide students through the admissions process and answer follow-up questions.

3. Developing – Predictive Analytics for At-Risk Students

• Current Practices: Advisors manually review academic progress reports and retention data to flag struggling students.
• Common Issues: Interventions happen too late—once students are already disengaged or at risk of dropping out.
• AI to Explore: AI-driven retention models that analyze student behaviors and proactively alert advisors for early intervention, improving student success rates.

4. Established – Proactive Advising & Student Engagement

• Current Practices: Schools implement faculty dashboards to track student progress but still rely on human-led interventions.
• Common Issues: Students must take the initiative to seek help—institutions react, rather than anticipate needs.
• AI to Explore: AI-powered nudging systems that send personalized reminders for assignments, deadlines, and support resources, keeping students on track.

5. Optimized – Fully Personalized Student Experience

• Current Practices: Academic advising remains manual, with recommendations based on general degree pathways rather than individual goals.
• Common Issues: Students struggle to see the connection between their coursework, career goals, and personal aspirations.
• AI to Explore: AI-driven recommendation engines that suggest courses, extracurriculars, internships, and career paths tailored to individual student preferences and academic progress.

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How Higher Ed Leaders Can Take Action

To move toward AI maturity in student engagement, institutions should:

1. Assess their current AI readiness start the conversation from within before it comes from outsiders based on poor student outcomes.
2. Identify key AI touchpoints in the student journey where automation and personalization can have the most impact.
3. Invest in AI-powered engagement tools - like Element451’s chatbots, predictive analytics, and automated communication solutions. See our Customer Success Stories to understand why this isn't a shameless plug: https://element451.com/customers or more in-depth success stories at https://www.enrollify.org/podcasts/in-your-element
4. Train staff and faculty to use AI effectively, ensuring adoption across departments.

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The Path Forward

AI is no longer a futuristic concept—it is a necessary tool for institutions seeking to enhance student engagement, improve retention, and deliver a truly personalized experience. The Student Success Lifecycle is the first step in a broader AI adoption journey.